Gene-drug Pairs Research Articles

Pharmacogenomic (PGx) Counseling: Exploring Participant Questions about PGx Test Results.

As pharmacogenomic (PGx) use in healthcare increases, a better understanding of patient needs will be necessary to guide PGx result delivery. The Coriell Personalized Medicine Collaborative (CPMC) is a prospective study investigating the utility of personalized medicine. Participants received online genetic risk reports for 27 potentially actionable complex diseases and 7 drug–gene pairs and could request free, telephone-based genetic counseling (GC). To explore the needs of individuals receiving PGx results, we conducted a retrospective qualitative review of inquiries from CPMC participants who requested counseling from March 2009 to February 2017. Eighty out of 690 (12%) total GC inquiries were focused on the discussion of PGx results, and six salient themes emerged: “general help”, “issues with drugs”, “relevant disease experience”, “what do I do now?”, “sharing results”, and “other drugs”. The number of reported medications with a corresponding PGx result and participant engagement were significantly associated with PGx GC requests (p < 0.01 and p < 0.02, respectively). Our work illustrates a range of questions raised by study participants receiving PGx test results, most of which were addressed by a genetic counselor with few requiring referrals to prescribing providers or pharmacists. These results further support a role for genetic counselors in the team-based approach to optimal PGx result delivery.

Drug Use in Denmark for Drugs Having Pharmacogenomics (PGx) Based Dosing Guidelines from CPIC or DPWG for CYP2D6 and CYP2C19 Drug-Gene Pairs: Perspectives for Introducing PGx Test to Polypharmacy Patients.

Background: The cytochrome P450 drug metabolizing enzymes CYP2D6 and CYP2C19 are the major targets for pharmacogenomics (PGx) testing and determining for drug response. Clinical dosing guidelines for specific drug-gene interactions (DGI) are publicly available through PharmGKB. The aim of this register study was to map the use of drugs in Denmark for drugs having actionable dosing guidelines (AG) i.e., dosing recommendations different from standard dosing for CYP2D6 or CYP2C19 DGI in terms of consumption. Methods: The Danish Register of Medicinal Product Statistics was the source to retrieve consumption in Defined Daily Dose (DDD) i.e., the assumed average maintenance dose per day for a drug used for its main indication in adults and number of users (2017 data). Clinical dosing guidelines were available from the PharmGKB website. Results: Forty-nine drugs have guidelines corresponding to 14.5% of total sales in DDD. Twenty-eight drugs have AG corresponding to 375.2 million DDD. Pantoprazole, lansoprazole, omeprazole, clopidogrel, and metoprolol constituted fifty-eight percent of the consumption in DDD of drugs having AG. The consumption of antidepressant drugs, opioids, and antipsychotic drugs were 157.0 million DDD; with 441,850 users, 48.9 million DDD; with 427,765 users, and 23.7 million DDD; with 128,935 users, respectively. Age distributions of consumption of drugs and drug combinations, e.g., for sertraline redeemed either alone or in combination with metoprolol and tramadol, are presented. Conclusion: This exploratory register study clearly showed that a large fraction of the Danish population, especially the elderly, are exposed to drugs or drug combinations for which there exist AG related to PGx of CYP2D6 or CYP2C19.

Longitudinal Analysis of Gene Expression Changes During Cervical Carcinogenesis Reveals Potential Therapeutic Targets.

Despite advances in the treatment of cervical cancer (CC), the prognosis of patients with CC remains to be improved. This study aimed to explore candidate gene targets for CC. CC datasets were downloaded from the Gene Expression Omnibus database. Genes with similar expression trends in varying steps of CC development were clustered using Short Time-series Expression Miner (STEM) software. Gene functions were then analyzed using the Gene Ontology (GO) database and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Protein interactions among genes of interest were predicted, followed by drug-target genes and prognosis-associated genes. The expressions of the predicted genes were determined using real-time quantitative polymerase chain reaction (RT-qPCR) and Western blotting. Red and green profiles with upward and downward gene expressions, respectively, were screened using STEM software. Genes with increased expression were significantly enriched in DNA replication, cell-cycle-related biological processes, and the p53 signaling pathway. Based on the predicted results of the Drug-Gene Interaction database, 17 drug-gene interaction pairs, including 3 red profile genes (TOP2A, RRM2, and POLA1) and 16 drugs, were obtained. The Cancer Genome Atlas data analysis showed that high POLA1 expression was significantly correlated with prolonged survival, indicating that POLA1 is protective against CC. RT-qPCR and Western blotting showed that the expressions of TOP2A, RRM2, and POLA1 gradually increased in the multistep process of CC. TOP2A, RRM2, and POLA1 may be targets for the treatment of CC. However, many studies are needed to validate our findings.

Coverage of pharmacogenetic tests by private health insurance companies

ObjectiveTo assess the coverage of clinically relevant pharmacogenetic tests by the top 41 private insurance companies in the United States. DesignWebsites of insurance companies were searched for medical policies addressing 34 common and clinically relevant pharmacogenetic tests referenced by the Clinical Pharmacogenetics Implementation Consortium, PharmGKB, and Food and Drug Administration product labeling. Those policies were subsequently reviewed for the coverage of the tests by gene-drug pair and by company. Policies were subsequently reviewed to determine coverage of pharmacogenetic tests by gene-drug indication group (GDIG) and an insurance company. Settings and participantsNot applicable. Outcome measuresWithin unique policy sets, the following were analyzed: (1) the number of times each GDIG was mentioned; (2) the percentage of times each GDIG was mentioned; (3) when mentioned, the number of times each GDIG was covered; (4) when mentioned, the percentage of times each GDIG was covered; and (5) regardless of being mentioned, the percentage of times each GDIG was covered. ResultsA total of 223 medical policies mentioning pharmacogenetic tests were retrieved, representing 34 unique policy sets from 41 companies. Thirty-three companies had their policies accessible on their website. Approximately 50% of GDIGs were unanimously mentioned in all policies but were covered only < 20% of the time. When mentioned in a policy, 7 GDIGs were uniformly covered, and 11 GDIGs were uniformly not covered. Overall, insurance companies covered approximately 40% of GDIGs mentioned in their policies. ConclusionThe medical policies addressing recommended pharmacogenetic tests were not readily accessible on websites of the top private health insurance companies. The coverage and payments of the tests varied by the company and gene-drug pairs and remain suboptimal.

Unveiling the guidance heterogeneity for genome-informed drug treatment interventions among regulatory bodies and research consortia

Pharmacogenomics and personalized medicine interventions hold promise to optimize drug treatment modalities and hence, improve the quality of life of the patients by minimizing the occurrence of adverse drug reactions and/or maximizing drug treatment efficacy. To this end, proper guidance for accurately prescribing the correct drug at the right dose is empowered by major regulatory bodies, namely the U.S. Food and Drug Administration (FDA) and the European Medicine Agency (EMA), and well-recognized research consortia, like the Clinical Pharmacogenetics Implementation Consortium (CPIC), that propose therapeutic recommendations after the thorough evaluation of the existing scientific evidence base. In this context, the consistency of these recommendations is crucial for smoothly integrating pharmacogenomics into the clinic. Here, we collected all of the important and clinically actionable pharmacogenomics information provided by the aforementioned renowned sources and documented it in order to assess potential similarities and, most importantly, differences. Our data show that the level of concordance regarding the guidance provided for the same drug-gene association pairs varies significantly, despite the fact that it all derives from a single evidence base. In particular, apart from the expected similarities in a number of association pairs, especially the ones related to cancer genomics, there are still major discrepancies that create confusion as to which guidance should be followed in order to properly inform drug prescribing. This regulatory deficiency calls for the fruitful engagement of the regulatory agencies involved with the contribution of other experts engaged in the field of pharmacogenomics in an effort to harmonize the existing arsenal of guidance for genome-informed drug prescription. The achievement of harmonization would in turn expedite bringing personalized medicine closer to clinical fruition.

Analysis of prognosis, genome, microbiome, and microbial metabolome in different sites of colorectal cancer

BackgroundThe colorectum includes ascending colon, transverse colon, descending colon, sigmoid colon, and rectum. Different sites of colorectal cancer (CRC) are different in many aspects, including clinical symptoms, biological behaviour, and prognosis.PurposeThis study aimed to analyse prognosis, genes, bacteria, fungi, and microbial metabolome in different sites of CRC.MethodsThe Surveillance, Epidemiology, and End Results (SEER) database and STAT were used to statistically describe and analyse the prognosis in different sites of CRC. RNA sequences of CRC from Broad Institute’s GDAC Firehose were re-annotated and reanalysed based on different sites using weighted gene co-expression network analysis (WGCNA). The Kaplan–Meier method was used to analyse the prognosis and Cytoscape was used to construct a drug-target network based on DGIdb databases. Bacterial 16S V3–V4 and fungal ITS V3–V4 ribosomal RNA genes of stool samples were sequenced. Gas chromatography/mass spectrometry (GS/MS) was performed to detect the microbial metabolites in stool samples. Bioinformatics analysis was performed to compare distinct gut microorganisms and microbial metabolites between rectal and sigmoid cancers.ResultsThe prognosis in CRC with different sites is significantly different. The closer to the anus predicted longer survival time. The difference between genes and co-expression pairs in CRC with different sites were constructed. The relative abundance of 112 mRNAs and 26 lncRNAs correlated with the sites of CRC were listed. Nine differentially expressed genes at different sites of CRC were correlated with prognosis. A drug-gene interaction network contained 227 drug-gene pairs were built. The relative abundance of gut bacteria and gut fungus, and the content of microbe-related metabolites were statistically different between rectal and sigmoid cancers.ConclusionsThere are many differences in prognosis, genome, drug targets, gut microbiome, and microbial metabolome in different colorectal cancer sites. These findings may improve our understanding of the role of the CRC sites in personalized and precision medicine.

Projected Cost-Effectiveness for 2 Gene-Drug Pairs Using a Multigene Panel for Patients Undergoing Percutaneous Coronary Intervention

BackgroundFor patients undergoing percutaneous coronary intervention, gene-drug associations exist relevant to first-line treatment options–antiplatelet agent, clopidogrel, and pain medication, tramadol. Knowledge of genotype information may allow for avoidance of adverse drug events during critical clinical windows. ObjectiveThis evaluation estimated cost-effectiveness associated with a multi-gene panel pre-emptively testing two genes providing CYP2C19 genotype-guided strategy for antiplatelet therapy, with CYP2D6 genotype-guided pain management, compared to single gene test for CYP2C19 with random assignment for pain treatment, and to no testing (empiric clopidogrel with random assignment for pain treatment). MethodsDecision analysis modeling was used to project costs from a payer perspective and patient quality-adjusted life years (QALYs) from the three strategies. The model captured composite risks of major adverse cardiovascular events and pain therapy-related adverse drug events and associated utility estimates. We conducted sensitivity analyses to assess influential input parameters. ResultsOver 15 months, multi-gene testing was least costly and yielded more QALYs compared to both single gene and no testing; total incremental costs were $1646 lower with incremental gains of 0.04 QALYs for multi-gene compared with single gene and $11 368 lower with 0.17 QALY gains compared to no test. Base case analyses revealed multi gene was dominant compared to both single gene and no test, as it demonstrated cost savings with increased QALYs. ConclusionsFor these patients, a multi-gene-guided strategy yields a favorable incremental cost-effectiveness ratio compared to the other two treatment strategies. Pre-emptively ascertaining additional gene-drug pair information can inform clinical and economic decision-making at the point of care.

Challenges and lessons learned from clinical pharmacogenetic implementation of multiple gene–drug pairs across ambulatory care settings

PurposeIncorporating a patient’s genotype into the clinical decision-making process is one approach to precision medicine. The University of Florida (UF) Health Precision Medicine Program is a pharmacist-led multidisciplinary effort that has led the clinical implementation of six gene–drug(s) pairs to date. This study focuses on the challenges encountered and lessons learned with implementing pharmacogenetic testing for three of these: CYP2D6-opioids, CYP2D6/CYP2C19-selective serotonin reuptake inhibitors, and CYP2C19-proton pump inhibitors within six pragmatic clinical trials at UF Health and partners. MethodsWe compared common measures collected within each of the pharmacogenetic implementations as well as solicited feedback from stakeholders to identify challenges, successes, and lessons learned. ResultsWe identified several challenges related to trial design and implementation, and learned valuable lessons. Most notably, case discussions are effective for prescriber education, prescribers need clear concise guidance on genotype-based actions, having genotype results available at the time of the patient–prescriber encounter helps optimize the ability to act on them, children prefer noninvasive sample collection, and study participants are willing to answer patient-reported outcomes questionnaires if they are not overly burdensome, among others. ConclusionThe lessons learned from implementing three gene–drug pairs in ambulatory care settings will help shape future pharmacogenetic clinical trials and clinical implementations.

Estimated nationwide impact of implementing a preemptive pharmacogenetic panel approach to guide drug prescribing in primary care in The Netherlands

BackgroundPharmacogenetics (PGx) is currently implemented in hospitals to optimize therapy with high-risk drugs. However, many drugs with dosing recommendations from the Dutch Pharmacogenetics Working Group and the Clinical Pharmacogenetics Implementation Consortium are used in primary care. Actionable phenotypes for the genes covered in these guidelines are common with estimates ranging from 85 to 95% of the population carrying at least one actionable phenotype. The goal of this study was to estimate the clinical impact of implementation of an upfront panel-based pharmacogenetic screening for eight genes related to drugs used in primary care for 2016.MethodsFor this study, dispensing data concerning first prescription for the period January 1–December 31, 2016, were combined with frequency data obtained in the “Implementation of Pharmacogenetics into Primary Care Project” (IP3) study to estimate the occurrence of actionable gene-drug pairs in daily practice in community pharmacies.ResultsIn 23.6% of all new prescriptions of 45 drugs (n = 856,002 new prescriptions/year), an actionable gene-drug interaction (GDI) was present according to the guidelines of the Dutch Pharmacogenetics Working Group. More importantly, these GDIs would result in a dose adjustment or switch to another drug in 5.4% of all new prescriptions.ConclusionsConsequently, with an anticipated near future where healthcare professionals will be regularly confronted with PGx test results, adjusting pharmacotherapy based on this information will become a routine task in healthcare.

Projected Prevalence of Actionable Pharmacogenetic Variants and Level A Drugs Prescribed Among US Veterans Health Administration Pharmacy Users

Implementation of pharmacogenetic testing to guide drug prescribing has potential to improve drug response and prevent adverse events. Robust data exist for more than 30 gene-drug pairs linking genotype to drug response phenotypes; however, it is unclear which pharmacogenetic tests, if implemented, would provide the greatest utility for a given patient population. To project the proportion of veterans in the US Veterans Health Administration (VHA) with actionable pharmacogenetic variants and evaluate how testing might be associated with prescribing decisions. This cross-sectional study included veterans who used national VHA pharmacy services from October 1, 2011, to September 30, 2017. Data analyses began April 26, 2018, and were completed February 6, 2019. Receipt of level A drugs based on VHA pharmacy dispensing records. Projected prevalence of actionable pharmacogenetic variants among VHA pharmacy users based on variant frequencies from the 1000 Genomes Project and veteran demographic characteristics; incident number of level A prescriptions, and proportion of new level A drug recipients projected to carry an actionable pharmacogenetic variant. During the study, 7 769 359 veterans (mean [SD] age, 58.1 [17.8] years; 7 021 504 [90.4%] men) used VHA pharmacy services. It was projected that 99% of VHA pharmacy users would carry at least 1 actionable pharmacogenetic variant. Among VHA pharmacy users, 4 259 153 (54.8%) received at least 1 level A drug with 1 188 124 (15.3%) receiving 2 drugs, and 912 189 (11.7%) receiving 3 or more drugs. The most common incident prescriptions during the study were tramadol (923 671 new recipients), simvastatin (533 928 new recipients), citalopram (266 952 new recipients), and warfarin (205 177 new recipients). Gene-drug interactions projected to have substantial clinical impacts in the VHA population include the interaction of SLCO1B1 with simvastatin (1 988 956 veterans [25.6%]), CYP2D6 with tramadol (318 544 veterans [4.1%]), and CYP2C9 or VKORC1 with warfarin (7 163 349 veterans [92.2%]). Clinically important pharmacogenetic variants are highly prevalent in the VHA population. Almost all veterans would carry an actionable variant, and more than half of the population had been exposed to a drug affected by these variants. These results suggest that pharmacogenetic testing has the potential to affect pharmacotherapy decisions for commonly prescribed outpatient medications for many veterans.

Pharmacogenetic Factors Affecting Asthma Treatment Response. Potential Implications for Drug Therapy.

Asthma is a frequent disease, mainly characterized by airway inflammation, in which drug therapy is crucial in its management. The potential of pharmacogenomics testing in asthma therapy has been, to date, little explored. In this review, we discuss pharmacogenetic factors affecting asthma treatment, both related to drugs used as controller medications for regular maintenance, such as inhaled corticosteroids, anti-leukotriene agents, long-acting beta-agonists, and the new biologic agents used to treat severe persistent asthma. In addition, we discuss current pharmacogenomics knowledge for rescue medications provided to all patients for as-needed relief, such as short-acting beta-agonists. Evidence for genetic variations as a factor related to drugs response has been provided for the following genes and groups of drugs: Inhaled corticosteroids: FCER2; anti-leukotriene agents: ABCC1, and LTC4S; beta-agonists: ADRB2. However, the following genes require further studies confirming or rejecting association with the response to asthma therapy: ADCY9, ALOX5, ARG1, ARG2, CRHR1, CRHR2, CYP3A4, CYP3A5, CYSLTR1, CYSLTR2, GLCCI1, IL4RA, LTA4H, ORMDL3, SLCO2B1, SPATS2L, STIP1, T, TBX21, THRA, THRB, and VEGFA. Although only a minority of these genes are, at present, listed as associated with drugs used in asthma therapy, in the Clinical Pharmacogenomics Implementation Consortium gene-drug pair list, this review reveals that sufficient evidence to start testing the potential of clinical pharmacogenomics in asthma therapy already exists. This evidence supports the inclusion in pilot pharmacogenetics tests of at least four genes. Hopefully these tests, if proven useful, will increase the efficiency and the safety of asthma therapy.

Commercial Pharmacogenetic Tests in Psychiatry: Do they Facilitate the Implementation of Pharmacogenetic Dosing Guidelines?

Expert groups have created dosing guidelines to facilitate the implementation of pharmacogenetic knowledge into clinical practice and commercial pharmacogenetic tests are becoming increasingly accessible. However, the extent to which these commercial tests facilitate the implementation of dosing guidelines is not clear. Gene-drug pairs included on 22 commercial pharmacogenetic test panels were extracted and cross-referenced with the 74 gene-drug pairs with dosing guidelines in the Pharmacogenetics Knowledgebase, with particular attention given to the 28 gene-drug pairs relevant to psychiatry. On average, 70% of the 28 gene-drug pairs most relevant to psychiatry were covered by the examined tests. Six gene-drug pairs (CYP2D6-venlafaxine, CYP2D6-paroxetine, CYP2D6-amitriptyline, CYP2C19-sertraline, CYP2C19-citalopram, CYP2C19-amitriptyline) were included by all tests. Gene-drug pairs included on less than half of the test panels included HLA-B-phenytoin (14%), HLA-A-carbamazepine (24%), HLA-B-carbamazepine (29%), and CYP2D6-zuclopenthixol (43%). Most commercial pharmacogenetic tests we examined are well-equipped to facilitate implementation of the majority of dosing guidelines relevant to psychiatry but are limited in their ability to facilitate implementation of the full spectrum of dosing guidelines currently available.

Combined evaluation of genotype and phenotype of thiopurine S-methyltransferase (TPMT) in the clinical management of patients in chronic therapy with azathioprine.

Background The thiopurine S-methyltransferase (TPMT)/azathioprine (AZA) gene-drug pair is one of the most well-known pharmacogenetic markers. Despite this, few studies investigated the implementation of TPMT testing and the combined evaluation of genotype and phenotype in multidisciplinary clinical settings where patients are undergoing chronic therapy with AZA. Methods A total of 356 AZA-treated patients for chronic autoimmune diseases were enrolled. DNA was isolated from whole blood and the samples were analyzed for the c.460G>A and c.719A>G variants by the restriction fragment length polymorphism (RFLP) technique and sequenced for the c.238G>C variant. The TPMT enzyme activity was determined in erythrocytes by a high-performance liquid chromatography (HPLC) assay. Results All the patients enrolled were genotyped while the TPMT enzyme activity was assessed in 41 patients. Clinical information was available on 181 patients. We found no significant difference in the odds of having adverse drug reactions (ADRs) in wild-type patients and variant allele carriers, but the latter had an extra risk of experiencing hematologically adverse events. The enzyme activity was significantly associated to genotype. Conclusions TPMT variant allele carriers have an extra risk of experiencing hematologically adverse events compared to wild-type patients. Interestingly, only two out of 30 (6.6%) patients had discordant results between genotype, phenotype and onset of ADRs.

Economic Value of Pharmacogenetic Testing for Cancer Drugs with Clinically Relevant Drug-Gene Associations: A Systematic Literature Review.

Pharmacogenetic testing can provide predictive insights about the efficacy and safety of drugs used in cancer treatment. Although many drug-gene associations have been reported in the literature, the strength of evidence supporting each association can vary significantly. Even among the subgroup of drugs classified by the PharmGKB database to have a high or moderate level of evidence, there is limited information regarding the economic value of pharmacogenetic testing. To: (a) summarize the available pharmacoeconomic evidence assessing the value of pharmacogenetic testing for cancer drugs with clinically relevant drug-gene associations; (b) determine the quality of the studies that contain this evidence; and (c) discuss the quality of this evidence with respect to the level of evidence of the drug-gene associations. The PharmGKB database was used to identify cancer drugs with clinically relevant drug-gene associations graded high (1A, 1B) or moderate (2A, 2B). A systematic literature review was conducted using these drugs. Ovid MEDLINE and Embase databases were searched to identify cost-effectiveness, cost-utility, or cost-minimization studies comparing pharmacogenetic testing to an alternative. Cost and effect values from every relevant comparison within the studies were extracted, and the incremental cost-effectiveness ratio (ICER) was either extracted or calculated for each comparison. Quality assessment was conducted for each study using the Quality of Health Economic Studies (QHES) instrument. Qualitative synthesis was used to summarize the data. The search yielded 2,191 citations, of which 35 studies met the inclusion criteria. Pharmacoeconomic studies were available for the following drugs from the PharmGKB database: fluoropyrimidine, 6-mercaptopurine, irinotecan, carboplatin, cisplatin, erlotinib, gefitinib, cetuximab, panitumumab, and trastuzumab. The studies were conducted in Asia, Europe, Canada, the United States, and Mexico and reported cost-utility, cost-effectiveness, and cost-minimization outcomes. The mean QHES score was 80 (SD = 22) for the studies of drug-gene pairs with high (1A, 1B) and moderate (2A, 2B) levels of evidence (1A = 82, 1B = 93, 2A = 71, and 2B = 74). There was variation across studies in terms of reporting. 109 relevant comparisons were identified within the studies. Of those that reported cost per life-year or cost per quality-adjusted life-year (n = 58 comparisons), pharmacogenetic testing was dominant in 21% overall and 42%, 21%, 17%, and 5% of the comparisons in Asia, Europe, Canada, and the United States, respectively. Variability was observed in the ICER values regardless of geographic region or drug. Pharmacogenetic testing was cost saving in 17 of 19 cost-minimization comparisons and was favored most frequently when compared with genetically indiscriminate strategies containing the drug of interest. There was mixed evidence regarding the value of pharmacogenetic testing to guide cancer treatment. For future pharmacogenomic-related economic studies, we recommend prioritizing clinically relevant drug-gene associations and greater adherence to available best practice guidelines for conducting and reporting economic evaluation studies. No outside funding supported this review. Part of Hussain's research time was supported by a Merit Review Award (I01 BX000545), Medical Research Service, U.S. Department of Veterans Affairs. Hussain also reports personal fees from Bristol-Myers Squibb, AstraZeneca, Novartis, Bayer HealthCare Pharmaceuticals, and France Foundation, outside the submitted work. Onukwugha reports grants from Pfizer and Bayer HealthCare Pharmaceuticals, along with advisory board fees from Novo Nordisk, outside the submitted work. Faruque, Neuberger, and Noh have nothing to disclose.

Pharmacogenomic Update On Antidepressant and Antipsychotic Medications

Psychiatric medications continue to be prescribed on a ‘trial-and-error’ fashion, with virtually no predictive tools available allowing to select type and dose of medications for any given individual.An increasing amount of evidence support an important role for genetic markers to improve outcome to many antidepressant and antipsychotic used for depression and schizophrenia, respectively. High levels of clinical evidence in favor of genetic associations are particularly reported for drug metabolizing genes. Another example are patients of Asian ancestry who receive carbamazepine and where the HLA-B*1502 marker substantially increases risk of serious skin disorders (Stevens Johnson Syndrome and toxic epidermal necrolysis), leading to policies where genetic testing is now mandatory in some Asian countries.This presentation will begin by reviewing the state of the current research with a focus on drug metabolizing enzymes and highlight expert consensus guidelines and recommendations provided by national drug and safety administrative institutions.CYP450 enzymes, and in particular CYP2D6 and CYP2C19, are responsible for metabolizing most psychiatric medications. Data will be shown from 383 physicians (mostly psychiatrists and family general practitioners) from the greater Toronto area returning surveys following genetic testing for CYP2D6 and CYP2C19 genes (among others) of their patients treated with antidepressants and antipsychotic medications. Questionnaires where retrieved 6-8 weeks later and results indicate that whenever genetic information was considered in their treatment decisions, improvement of drug treatment was seen in 122 cases compared to only 2 cases where a slight symptom deterioration was reported (p < 0.01).Next, results from genetic analyses in noradrenergic and serotonergic genes will be shown from 350 adults diagnosed with late life depression (LLD). Participants received open-label venlafaxine, a serotonin-norepinephrine reuptake inhibitor, for up to 12 weeks. After adjusting for multiple comparisons, the norepinephrine variant rs2242446 (T-182C) was significantly associated with remission (odds ratio=1.66, 95% CI=1.13, 2.42). Individuals with the rs2242446 C/C genotype were more likely to remit (73.1%) than those with either the C/T (51.8%) or the T/T genotype (47.3%). Individuals with the C/C genotype also had a shorter time to remission than those with the C/T or T/T genotypes and had a greater percentage change in depressive symptom scores from baseline to end of treatment (up to week 12). We are currently testing selected microRNA plasma level changes at baseline and end of treatment and these results will be presented at the conference.Overall, pharmacogenomics is being recognized by many stakeholders to bear the potential to improve psychiatric medication treatments. While this notion has become increasingly supported for some important gene-drug pairs through thorough reviews provided by expert panels, more research is required to develop, improve and validate multi-gene algorithms in order to overcome the current trial-and-error approaches in psychiatric medicine. Limitations such as lack of consensus' to select for actionable gene-drug pairs, which genotypes best to select, how to assign metabolizer status and how to effectively develop algorithms to guide treatment decisions will be discussed.

A Practical First Step Using Needs Assessment and a Survey Approach to Implementing a Clinical Pharmacogenomics Consult Service.

Genetic-guided selection of non-oncologic medications is not commonly practiced in general, and at University of California, San Francisco (UCSF) Health, specifically. Understanding the unique position of clinicians with respect to clinical pharmacogenetics (PG) at a specific institution or practice is fundamental for implementing a successful PG consult service. To assess clinicians' current practices, needs, and interests with respect to clinical PG at UCSF Health, a large tertiary academic medical center. A list of 42 target medications with clinical PG recommendations was complied. Clinical specialties that routinely used the target medications were identified. A 12-question survey focused on practice of PG for target medications was developed. Pharmacists and physicians were surveyed anonymously in several clinical specialties. Survey results were analyzed using descriptive statistics. Of the 396 clinicians surveyed, 76 physicians and 59 pharmacists participated, resulting in 27% and 50% average response rates, respectively. The current use of PG in clinical practice for physicians and pharmacists was 29% and 32%, respectively, however this number varied across clinical specialties from 0% to 80%. Of clinicians whom reported they do not currently apply PG, 63% of physicians and 54% of pharmacists expressed interest in integrating PG. However, the level of interest varied from 20% to 100% across specialties. Of the respondents, 64% of physicians and 56% of pharmacists elected to provide contact information to investigators to further discuss their interest related to clinical PG. While PG is not uniformly practiced at UCSF Health, there is considerable interest in utilizing PG by the respondents. Our approach was successful at identifying clinicians and services interested in PG for specific drug-gene pairs. This work has set a foundation for next steps to advance PG integration at UCSF Health. Clinicians can adopt our approach as preliminary work to build a clinical PG program at their institutions.

Genetics of perioperative pain management.

The current review will discuss the current literature on genetics of pain and analgesia, with special emphasis on perioperative setting. We will also discuss pharmacogenetics-based management guidelines, current clinical status and future perspectives. Recent literature suggests that the interindividual variability in pain and postoperative analgesic response is at least in part because of one's genetic make-up. Some of the well characterized polymorphisms that are associated with surgical pain and opioid-related postoperative adverse outcomes are described in catechol-O-methyl transferase, CYP2D6 and μ-opioid receptor (OPRM1), ATP-binding cassette subfamily B member 1, ABCC3, organic cation transporter 1 genes. Clinical Pharmacogenetics Implementation Consortium has put forth recommendations on CYP2D6 genotype-based opioid selection and dosing. The list of drug-gene pairs studied continue to expand. Pharmacogenetic approach marks the dawn of personalized pain medicine both in perioperative and chronic pain settings.

Genetic variation in the Estonian population: pharmacogenomics study of adverse drug effects using electronic health records

Pharmacogenomics aims to tailor pharmacological treatment to each individual by considering associations between genetic polymorphisms and adverse drug effects (ADEs). With technological advances, pharmacogenomic research has evolved from candidate gene analyses to genome-wide association studies. Here, we integrate deep whole-genome sequencing (WGS) information with drug prescription and ADE data from Estonian electronic health record (EHR) databases to evaluate genome- and pharmacome-wide associations on an unprecedented scale. We leveraged WGS data of 2240 Estonian Biobank participants and imputed all single-nucleotide variants (SNVs) with allele counts over 2 for 13,986 genotyped participants. Overall, we identified 41 (10 novel) loss-of-function and 567 (134 novel) missense variants in 64 very important pharmacogenes. The majority of the detected variants were very rare with frequencies below 0.05%, and 6 of the novel loss-of-function and 99 of the missense variants were only detected as single alleles (allele count = 1). We also validated documented pharmacogenetic associations and detected new independent variants in known gene-drug pairs. Specifically, we found that CTNNA3 was associated with myositis and myopathies among individuals taking nonsteroidal anti-inflammatory oxicams and replicated this finding in an extended cohort of 706 individuals. These findings illustrate that population-based WGS-coupled EHRs are a useful tool for biomarker discovery.

Clinical Pharmacogenetics for Precision Medicine: Successes and Setbacks.

Pharmacogenetics is a key component in the delivery of therapeutics to maximize pharmacologic efficacy and minimize toxicity. There are numerous identified gene-drug pairs that demonstrate the utility of pharmacogenetics testing for drug or dose selection. Although some of these pairs have translated into clinical use, pharmacogenetic testing has not yet made its way into routine clinical practice at many institutions. This review provides an overview of clinically actionable pharmacogenetics in precision medicine. Examples of successfully implemented gene-drug pairs, along with common testing methodologies and guidelines for application, are discussed. Remaining barriers to widespread clinical implementation are also examined. There is a recognized role for genotyping in the guidance of therapeutic drug regimens and the prevention of adverse drug reactions. Evidence-based guidelines are available to aid in the selection of treatment upon pharmacogenetics testing for established gene-drug pairs. Multidisciplinary clinical collaboration and clinical decision support tools will be critical for widespread adoption, and financial reimbursement barriers remain.

Association of Interleukin 6 Receptor Variant With Cardiovascular Disease Effects of Interleukin 6 Receptor Blocking Therapy

Electronic health record (EHR) biobanks containing clinical and genomic data on large numbers of individuals have great potential to inform drug discovery. Individuals with interleukin 6 receptor (IL6R) single-nucleotide polymorphisms (SNPs) who are not receiving IL6R blocking therapy have biomarker profiles similar to those treated with IL6R blockers. This gene-drug pair provides an example to test whether associations of IL6R SNPs with a broad range of phenotypes can inform which diseases may benefit from treatment with IL6R blockade. To determine whether screening for clinical associations with the IL6R SNP in a phenome-wide association study (PheWAS) using EHR biobank data can identify drug effects from IL6R clinical trials. Diagnosis codes and routine laboratory measurements were extracted from the VA Million Veteran Program (MVP); diagnosis codes were mapped to phenotype groups using published PheWAS methods. A PheWAS was performed by fitting logistic regression models for testing associations of the IL6R SNPs with 1342 phenotype groups and by fitting linear regression models for testing associations of the IL6R SNP with 26 routine laboratory measurements. Significance was reported using a false discovery rate of 0.05 or less. Findings were replicated in 2 independent cohorts using UK Biobank and Vanderbilt University Biobank data. The Million Veteran Program included 332 799 US veterans; the UK Biobank, 408 455 individuals from the general population of the United Kingdom; and the Vanderbilt University Biobank, 13 835 patients from a tertiary care center. IL6R SNPs (rs2228145; rs4129267). Phenotypes defined by International Classification of Diseases, Ninth Revision codes. Of the 332 799 veterans included in the main cohort, 305 228 (91.7%) were men, and the mean (SD) age was 66.1 (13.6) years. The IL6R SNP was most strongly associated with a reduced risk of aortic aneurysm phenotypes (odds ratio, 0.87-0.90; 95% CI, 0.84-0.93) in the MVP. We observed known off-target effects of IL6R blockade from clinical trials (eg, higher hemoglobin level). The reduced risk for aortic aneurysms among those with the IL6R SNP in the MVP was replicated in the Vanderbilt University Biobank, and the reduced risk for coronary heart disease was replicated in the UK Biobank. In this proof-of-concept study, we demonstrated application of the PheWAS using large EHR biobanks to inform drug effects. The findings of an association of the IL6R SNP with reduced risk for aortic aneurysms correspond with the newest indication for IL6R blockade, giant cell arteritis, of which a major complication is aortic aneurysm.